Smart Toothbrush Position Monitoring via Accelerometer Statistical Modeling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current toothbrush monitoring systems lack accuracy in assessing toothbrushing technique, particularly in home environments, as they fail to provide comprehensive feedback on the temporal order and path taken during brushing, leading to potential neglect of certain mouth areas and inefficient dental care.
Innovation Solution
A method comprising a coaching phase where position and movement data are recorded to generate a user-specific statistical model, allowing for accurate monitoring of toothbrushing technique at home, including positional and temporal information, and a monitoring phase where this model is used to provide personalized feedback on brushing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If magnetic fields and magnetometers are used to determine precise positions of the toothbrush, then measurement precision is improved, but device complexity and ease of operation worsen
Solution Approach 1:
The patent replaces complex magnetic field-based position detection with a mechanical solution using an accelerometer and statistical modeling. Instead of using magnetometers and magnetic fields to directly measure toothbrush position, the system uses motion sensors to detect acceleration patterns and maps these to positional information through pre-established statistical models, thereby reducing device complexity while maintaining measurement capability
Solution Approach 2:
The patent creates a statistical model that copies or replicates the relationship between motion patterns and toothbrush position. By training the model with actual brushing data, the system creates a virtual representation of position information that can be derived from accelerometer readings, eliminating the need for direct magnetic field measurement hardware in the toothbrush
2Ease of operation
If existing home-based monitoring systems are used, then ease of operation is improved, but measurement precision worsens
Solution Approach 1:
The patent performs preliminary training of the statistical model using actual user brushing data before the monitoring phase. By collecting and analyzing motion patterns during a training period, the system pre-establishes the relationship between accelerometer readings and toothbrush position for that specific user, thereby improving measurement precision for subsequent monitoring while maintaining home-based convenience
Solution Approach 2:
The patent transforms the approach by changing from direct position measurement to indirect position inference through motion pattern analysis. The system measures acceleration parameters and uses statistical models to derive position information, fundamentally changing the measurement parameters from direct spatial coordinates to motion-based derived positions, which improves both precision and ease of operation
3Ease of operation
If regions of the mouth are treated in isolation, then ease of operation is improved, but loss of information worsens
Solution Approach 1:
The patent implements continuous monitoring of toothbrush motion throughout the entire brushing session, capturing the temporal sequence of brushing actions. By continuously recording accelerometer data and mapping it to positional information over time, the system preserves the continuous journey of the toothbrush through different mouth regions, maintaining both simplicity and comprehensive information about brushing behavior
Data Source
Figure 1
Figure 2~3a
Figure 3b~3c
AI summary
A method of monitoring toothbrushing comprising: a coaching phase in which: a position sensor detects position information of a toothbrush during a first instance of free brushing by the user; one or more additional sensors record movement information of the toothbrush during the first instance of free brushing; a user-specific statistical model is generated which maps the positional information onto the movement information; and a monitoring phase in which: the one or more additional sensors record movement information of the toothbrush during a second instance of free brushing; and the toothbrush compares the movement information received during the second instance of free brushing with the user-specific statistical model to calculate positional information.